Effects of heterogeneous self-protection awareness on resource-epidemic coevolution dynamics

Xiaolong Chen; Kai Gong; Ruijie Wang; Shimin Cai; Wei Wang

doi:10.1016/j.amc.2020.125428

Effects of heterogeneous self-protection awareness on resource-epidemic coevolution dynamics

Appl Math Comput. 2020 Nov 15:385:125428. doi: 10.1016/j.amc.2020.125428. Epub 2020 Jun 20.

Authors

Xiaolong Chen^{1

2}, Kai Gong¹, Ruijie Wang³, Shimin Cai^{4

5

6}, Wei Wang⁷

Affiliations

¹ School of Economic Information Engineering, Southwestern University of Finance and Economics, Chengdu 611130, China.
² Financial Intelligence and Financial Engineering Key Laboratory of Sichuan Province, School of Economic Information Engineering, Chengdu 611130, China.
³ A Ba Teachers University, A Ba 623002, China.
⁴ School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China.
⁵ Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China.
⁶ Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 610054, China.
⁷ Cybersecurity Research Institute, Sichuan University, Chengdu 610065, China.

Abstract

Recent studies have demonstrated that the allocation of individual resources has a significant influence on the dynamics of epidemic spreading. In the real scenario, individuals have a different level of awareness for self-protection when facing the outbreak of an epidemic. To investigate the effects of the heterogeneous self-awareness distribution on the epidemic dynamics, we propose a resource-epidemic coevolution model in this paper. We first study the effects of the heterogeneous distributions of node degree and self-awareness on the epidemic dynamics on artificial networks. Through extensive simulations, we find that the heterogeneity of self-awareness distribution suppresses the outbreak of an epidemic, and the heterogeneity of degree distribution enhances the epidemic spreading. Next, we study how the correlation between node degree and self-awareness affects the epidemic dynamics. The results reveal that when the correlation is positive, the heterogeneity of self-awareness restrains the epidemic spreading. While, when there is a significant negative correlation, strong heterogeneous or strong homogeneous distribution of the self-awareness is not conducive for disease suppression. We find an optimal heterogeneity of self-awareness, at which the disease can be suppressed to the most extent. Further research shows that the epidemic threshold increases monotonously when the correlation changes from most negative to most positive, and a critical value of the correlation coefficient is found. When the coefficient is below the critical value, an optimal heterogeneity of self-awareness exists; otherwise, the epidemic threshold decreases monotonously with the decline of the self-awareness heterogeneity. At last, we verify the results on four typical real-world networks and find that the results on the real-world networks are consistent with those on the artificial network.

Keywords: Coevolution dynamics; Complex networks; Epidemic spreading; Resource allocation; Self-protection awareness.